Computer Science (CSCI)

D class assignments are only available on line at: myviterbi.usc.edu. Once you create your myViterbi profile, select the "D-Clearance Request Manager" to submit requests for CSCI courses. To be enrolled in an off-campus course, you MUST also be enrolled in the Distance Education Network (DEN). For more information, call 740-4488 or go to den.usc.edu. DEN courses are indicated by a location of DEN@Viterbi. For general questions regarding CSCI courses, you may email csdept@usc.edu.

A behind-the-scenes overview of the computational/algorithmic principles that form the basis of today's digital society. Exploration areas include social media, web search, videogames and location-based services.

General Education: This course satisfies the university's general education requirement.

Note: This is a GE-F Quantitative Reasoning course for NON-MAJORS. No credit will be awarded to CSCI, CECS, CSGM, or CSBA majors.

Object-oriented paradigm for programming-in-the-large in Java; writing sophisticated concurrent applications with animation and graphic user interfaces; using professional tools on team project. Prerequisite: CSCI 104L.

Intensive introduction to programming principles, discrete mathematics for computing, software design and software engineering concepts. Not available for credit to computer sciencemajors, graduate or undergraduate.

Design and implementation of networked games, from the origins of the supporting technologies in distributed systems, visual simulations, networked virtual environments, and shipped games. Recommended preparation: CSCI 420 or CSCI 580 or an equivalent course in graphics.

Explore the complex engineering process required to design and build a real-time graphics engine to support physical realism on mobile devices. Recommended preparation: CSCI 420 or CSCI 580 or an equivalent course in graphics.

Statistical methods for building intelligent and adaptive systems that improve performance from experiences; Focus on theoretical understanding of these methods and their computational implications. Recommended preparation: Undergraduate level training or coursework in linear algebra, multivariate calculus, basic probability and statistics; an undergraduate level course in Artificial Intelligence may be helpful but is not required.

Introduction of Ph.D. students to the broad range of computer science research. Two semesters registration required. Open to Computer Science doctoral students only. Graded CR/NC. Duplicates credit in former CSCI 597.

Restriction: Registration open to the following major(s): Computer Science

Restriction: Registration open to the following class level(s): Doctoral Student

Practical principles for the long-term development of effective teaching in Computer Science. Intended for teaching assistants for classes offered by the Computer Science department. Graded CR/NC. Open only to Computer Science doctoral students.

Restriction: Registration open to the following major(s): Computer Science

Restriction: Registration open to the following class level(s): Doctoral Student